IoTSC2014 – Day 4: CONSUME

The last technical day at the IoTSC2014 was covering topics in the CONSUME area or either said – collecting and parsing sensor data. It was a very exciting day, also including a socially oriented event for dinner.

We began the day with going through the history of human centric sensing in the modern era. We went through the early 90s, where the RFID badges flourished, first indoor-location tracking projects surfaced and, of course, people started wondering about their privacy for the first time.

As we stepped in the early 2000s the focus of acceptability on sensing was still limited. First devices with accelerometer and gyro surfaced, laying foundation to what we call physical activities trackers today. This is the period where the WSN [Wireless Sensor Network] first appeared as a conception.

Nowadays, most accurate and widespread WSN is already located around us. Everyone of us carry a phone, right? In the beginning of this year, for example – the US has officially become a smartphone nation, Nielsen reports.

The research group’s latest Digital Consumer Report estimates that 65 percent of all Americans owned one smartphone devices in 2013. That’s a big step up from 44 percent in 2011, and smartphones are now more common than game consoles (46 percent) and digital cable (54 percent). Americans are also increasingly tech-laden, with an average of four devices per person; 29 percent of them have a tablet versus just 5 percent two years ago.

We have had a good session with Dr. Christos Efstratiou[University of Kent] that put the focus on the so-called people-centric sensing and its evolution to citizen-centric on occasions. We have talked over community-centric sensing, as well as been given some examples on group activity sensing. I strongly recommend taking some time watching it as soon as from the University of Parma release the media.

After the lecture, as you may expect – coffee with all-sweet-things-you-can-have-in-Italy on the terrace. After grabbing a bite we were back to the hall getting deep into analyzing, modeling and predicting human behavior from mobile phone data. All these mobile phones produce large amount of data and there is crying need for algorithms to “read” it correctly and efficiently. drawing high-quality conclusions out. Here is where Dr. Mirco Musolesi[University of Birmingham]. kicked in with some real-time examples of analyzing geodata and indoor-tracking experiments.

Click the image below to get through one of the aspects we have talked about – the so-called Spatial Matrix, which is the foundation in predicting human mobility.

We had two hands-on sessions – one with Dr. Efstratiou which brought us through exporting and plotting info from datasets containing two different states of people – either standing or in motion; the second hand-on was led by Dr. Musolesi and wasn’t exactly a hands-on, but a nice presentation of various Python libraries, ports and frameworks.

Sadly, this was the last day with technical talks on the IoT & Smart Cities Ph.D. School 2014. It completes the whole picture, though – after learning about CONNECT and COLLECT, indeed the next step is to CONSUME it.

I am now working on an article, giving my final assessment of the Internet of Things and Smart Cities Ph.D. School 2014 experience. In in the meantime, I am getting into the IOT360 blog contest, I guess that the IoTSC2014 summary will be out on Monday. Or, earlier – watch out!